The Masters in Mathematics/Applied Mathematics offers courses, taught by experts, across a wide range. Mathematics is highly developed yet continually growing, providing new insights and applications. It is the medium for expressing knowledge about many physical phenomena and is concerned with patterns, systems, and structures unrestricted by any specific application, but also allows for applications across many disciplines.
Modes of delivery of the Masters in Mathematics/Applied Mathematics include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in project work.
If you are studying for the MSc you will take a total of 120 credits from a mixture of Level-4 Honours courses, Level-M courses and courses delivered by the Scottish Mathematical Sciences Training Centre (SMSTC).
You will take courses worth a minimum of 90 credits from Level-M courses and those delivered by the SMSTC. The remaining 30 credits may be chosen from final-year Level-H courses. The Level-M courses offered in a particular session will depend on student demand. Below are courses currently offered at these levels, but the options may vary from year to year.
The project titles are offered each year by academic staff and so change annually.
Career opportunities are diverse and varied and include academia, teaching, industry and finance.
Graduates of this programme have gone on to positions such as:
Maths Tutor at a university.
This programme is now closed but you may want to consider other courses such as the Mathematics MSc.
The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.
Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management
Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.
Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.
The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.
Bloomberg terminal laboratory
King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.
You will use the Bloomberg terminals to:
The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.
We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.
This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
Average per week: Three hours for 11 weeks per each 15 credit module.
You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).
The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.
Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Mathematics and Computing for Finance at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
The MSc Mathematics and Computing for Finance course has been designed to meet the growing demand for specially trained mathematicians to work in the world’s financial markets and insurance.
Despite the current volatile nature of the banking industry, many banks still have a pressing need for employees with advanced mathematical skills who can further their understanding of turbulence in financial markets.
On the Mathematics and Computing for Finance course you will study different elements of both mathematics and computing in addition to developing your communication and presentational skills through a project you will undertake. As a student of the MSc in Mathematics and Computing for Finance programme you will be fully supported to ensure that your project is best suited to support your future career plans.
Have in depth knowledge in stochastic analysis and parts of advanced real analysis. (Fourier analysis and Partial Differential Equations) as well as parts of numerical analysis which are central for applications to finance.
Have developed advanced computing skills being essential for handling problems relevant for a job on the finance markets.
Have, as a mathematician, a good understanding of finance markets.
Have developed skills needed to work in a highly inter-disciplinary profession, including advanced programming techniques and communication skills across the borders.
Please visit our website for a full description of modules for the MSc Mathematics and Computing for Finance.
The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistically analysis, marketing and sales.
Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.
The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.
All academic staff in Mathematics are active researchers and the department has a thriving research culture.
"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."
Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance
The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Expertise in the group encompasses a broad range of topics, including Continuum Mechanics, Analysis & Dynamical Systems, Industrial & Applied Mathematics, Inverse Problems, Mathematical Finance, and Numerical Analysis & Scientific Computing. The group has a strongly interdisciplinary research ethos, which it pursues in areas such as Mathematics in the Life Sciences, Uncertainty Quantification & Data Science, and within the Manchester Centre for Nonlinear Dynamics.
The Applied Mathematics group offers the MSc in Applied Mathematics as an entry point to graduate study. The MSc has two pathways, reflecting the existing strengths within the group in numerical analysis and in industrial mathematics. The MSc consists of five core modules (total 75 credits) covering the main areas of mathematical techniques, modelling and computing skills necessary to become a modern applied mathematician. Students then choose three options, chosen from specific pathways in numerical analysis and industrial modelling (total 45 credits). Finally, a dissertation (60 credits) is undertaken with supervision from a member of staff in the applied mathematics group with the possibility of co-supervision with an industrial sponsor.
The course aims to develop core skills in applied mathematics and allows students to specialise in industrial modelling or numerical analysis, in preparation for study towards a PhD or a career using mathematics within industry. An important element is the course regarding transferable skills which will link with academics and employers to deliver important skills for a successful transition to a research career or the industrial workplace.
The course features a transferable skills module, with guest lectures from industrial partners. Some dissertation projects and short internships will also be available with industry.
Students take eight taught modules and write a dissertation. The taught modules feature a variety of teaching methods, including lectures, coursework, and computing and modelling projects (both individually and in groups). The modules on Scientific Computing and Transferable Skills particularly involve significant project work. Modules are examined through both coursework and examinations.
Assessment comprises course work, exams in January and May, followed by a dissertation carried out and written up between June and September. The dissertation counts for 60 credits of the 180 credits and is chosen from a range of available projects, including projects suggested by industrial partners.
Course unit details
CORE (75 credits)
* Introduction to Uncertainty Quantification
* Mathematical Methods
* Partial Differential Equations
* Scientific Computing
* Transferable Skills for Applied Mathematicians
OPTIONAL (3 modules, 45 credits)
* Applied Dynamical Systems (IM)
* Continuum Mechanics (IM)
* Stability theory (IM)
* Transport Phenomena and Conservation Laws (IM)
* Advanced Uncertainty Quantification (IM,NA)
* Approximation Theory and Finite Element Analysis (NA)
* Numerical Linear Algebra (NA)
* Numerical Optimization and Inverse Problems (NA)
Students registered on the Numerical Analysis pathway must select modules marked NA, and those registered on the Industrial Modelling pathway must select modules marked IM.
Syllabuses for the modules Introduction to Uncertainty Quantification and Advanced Uncertainty Quantification are currently being finalized and details will be added here as soon as possible.
Modern computing facilities are available to support the course.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The programme will prepare students for a career in research (via entry into a PhD programme) or direct entry into industry. Possible subsequent PhD programmes would be those in mathematics, computer science, or one of the many science and engineering disciplines where applied mathematics is crucial. The programme develops many computational, analytical, and modelling skills, which are valued by a wide range of employers. Specialist skills in scientific computing are valued in the science, engineering, and financial sector.
The MSc in Mathematics is a one-year taught programme run by the School of Mathematics and Statistics. This programme is particularly suited for those seeking a career in academic mathematical research or a mathematics-related career in the private sector.
The programme consists of two semesters of taught courses followed by a dissertation (15,000 words) over the summer months. Most modules for the MSc in Mathematics are traditional semester-long lecture courses with end of semester exams, but some modules have a large element of continuous assessment. Class sizes range from 10 to 60 students, depending on the module.
The School of Mathematics and Statistics is well equipped with computing facilities (including a large parallel computing cluster) and an on-site library.
For an MSc in Mathematics, students take at least 90 credits at 5000-level Mathematics and Statistics modules. The remaining 30 credits can be taken from the School's 3000-level and 4000-level modules. At least 90 credits of the total of 120 credits of the taught part should be Pure Mathematics or Applied Mathematics modules.
The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2017–2018 academic year; some elements may be subject to change for 2018 entry.